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tf.config.experimental.set_memory_growth undefined / no effect

TensorFlow 2.x, GPU

CUDA OOM even on small batches; set_memory_growth call throws or is ignored.

What it means (root cause)

Memory growth must be set BEFORE any GPU device is initialized, and only the first visible device is configurable in some builds.

The symptom developers actually see: CUDA OOM even on small batches; set_memory_growth call throws or is ignored.

How to avoid it: Centralize device setup in one init function imported before everything else.

Step-by-step fix

Concrete, ordered steps from the dataset. Apply them in order; each line is a verified action, not generic advice.

  1. 1Call tf.config.experimental.set_memory_growth(gpu, True) immediately after tf.config.list_physical_devices('GPU') and before building the model.
  2. 2If the call errors, wrap in try/except and verify the GPU device list is non-empty.
  3. 3As an alternative for bounded allocation, set TF_GPU_ALLOCATOR=cuda_malloc_async.

Where this error appears

Languages, frameworks, and runtimes where this error is observed (from the 2026 DevFixPro error dataset, retrieved 2026-08-29):

TensorFlow 2.xGPU

TensorFlow 2.x on Linux/Windows with a CUDA GPU. The call is a no-op if issued after the first tensor allocation, which is why ordering matters.

How to prevent it & common questions

Practical prevention plus the questions developers ask most about this error.

What does "tf.config.experimental.set_memory_growth undefined / no effect" mean?

Memory growth must be set BEFORE any GPU device is initialized, and only the first visible device is configurable in some builds.

Which environments are affected by tf.config.experimental.set_memory_growth undefined / no effect?

TensorFlow 2.x, GPU

How do I fix tf.config.experimental.set_memory_growth undefined / no effect?

Call tf.config.experimental.set_memory_growth(gpu, True) immediately after tf.config.list_physical_devices('GPU') and before building the model. If the call errors, wrap in try/except and verify the GPU device list is non-empty. As an alternative for bounded allocation, set TF_GPU_ALLOCATOR=cuda_malloc_async.

How do I prevent tf.config.experimental.set_memory_growth undefined / no effect?

Centralize device setup in one init function imported before everything else.

Related DevFixPro tools

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● Data updated 2026-08-29

Sources & attribution

  • Error records aggregated from Google Search Console query gaps (2026-05-21~2026-08-18) for devfixpro.com, plus official framework docs (MDN, Node.js docs, Python docs, Go.dev, Rust book, Oracle Java docs, Docker docs, npm docs). Source dataset retrieved 2026-08-29. License: CC BY 4.0 — attribute DevFixPro (devfixpro.com).
  • Official reference: https://www.tensorflow.org/api_docs/python/tf/config/experimental/set_memory_growth
  • All cause, environment, fix and prevention text on this page is taken verbatim from the DevFixPro 2026 error dataset. DevFixPro does not invent root causes or fixes.
How this tf.config.experimental.set_memory_growth undefined / no effect page is built

Each error page is generated from a single record in the DevFixPro 2026 error dataset. The meaning, root cause, environments, fix steps, prevention, and official references are copied verbatim from that dataset and its official-doc sources; related-error links are computed from the error's category and explicit peer list. No root cause or fix is invented. The retrieval date for this dataset is 2026-08-29.

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